IT Co-Op Data Science - 2 roles (Ridgefield, CT, United States, Connecticut)
About this opportunity
Description
Boehringer Ingelheim is currently seeking a talented and innovative Data Science Co-Op candidate to join Central Data Science team at our Ridgefield, CT facility.
As a Data Science Co-Op, you will work on a global strategic initiative to make better use of our data and enhance our ability to make data driven decisions. You will work closely with business stakeholders to identify opportunities for leveraging data to drive business solutions, understand the business problem and extract relevant trends and patterns from data. You will help the team shape, develop, and execute complex analytic solutions that will transform the healthcare industry.
As an employee of Boehringer Ingelheim, you will actively contribute to the discovery, development and delivery of our products to our patients and customers. Our global presence provides opportunity for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the companies´ success. We realize that our strength and competitive advantage lie with our people. We support our employees in a number of ways to foster a healthy working environment, meaningful work, mobility, networking and work-life balance. Our competitive compensation and benefit programs reflect Boehringer Ingelheim´s high regard for our employees.
We look forward to receiving your application. Before applying please ensure you can commit to the following:
-Expect to be on-site for at least 3 days per week and must be located in the local area for the Co-op.
-Candidates will start in the time frame noted on the questions when you apply for this role.
-Co-op Students will work for at least 4 months after the start date. We may extend you up to 6 months in total depending on business needs. These are Full time positions.
Duties & Responsibilities
The primary focus of the Data Science Co-Op candidate will be to work with a business team to analyze data sets and design analytical solutions. Responsibilities include translating idea to data, data preparation, analysis and modelling, user testing, product development and maintenance.
Requirements
Must be a current undergraduate, graduate or advanced degree student in good academic standing.
Student must be enrolled at an accredited college or university for the duration of the internship/co-op.
Overall cumulative minimum GPA from last completed quarter/semester 3.0 GPA (on a 4.0 scale) preferred.
Major or minor in related field of internship/co-op.
Undergraduate students must have completed at least 12 credit hours at current college or university.
Graduate and advanced degree students must have completed at least 9 credit hours at current college or university.
Eligibility Requirements :
Must be legally authorized to work in the United States without restriction.
Must be willing to take a drug test and post-offer physical (if required).
Must be 18 years of age or older.
Desired Skills, Experience and Abilities
Experience with Data Visualization Tools
Strong command of Microsoft Excel and PowerPoint
Proficient in Python and or R, SQL
Understanding of database and analytical technologies in the industry
Experience or coursework in machine learning and/or deep learning packages available for R and Python
Demonstrated ability to think strategically about business, product and technical challenges in an enterprise environment
Ability to collaborate in a team environment and excel working in a VUCA environment
Strong oral and written communication skills
Experience with large data sets and distributed computing (Hive/Hadoop) is a plus.
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Job details
How this role compares
Computed from every other active Biostatistics & Data Science role in our database, not just this employer's listings.
We currently track 25 comparable Intern/Fellow/Postdoc Biostatistics & Data Science roles across 9 biopharma companies.
Salary context
6 of 25 peers report a salary range (USD, annualized)
Peers share this role's job function and a matching or adjacent seniority level -- not necessarily the same therapeutic area or country.
Where these roles are based
Top locations among the 25 comparable roles
Seniority mix
25 of 25 peers have a known seniority level
Therapeutic area mix
0 of 25 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden
No peers with a known therapeutic area yet.
Similar opportunities
The closest matches from our peer group, ranked by how similar they are, not how well you'd qualify for them -- treat this as market context, not a guaranteed shortlist; a weak match is labeled as one below.
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How we calculate "similar"
No black box, no LLM guesswork: a deterministic score built from four normalized attributes. Here's this role's own peer group at different match levels, so you can see the mechanism, not just the result.
Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.
0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.